Project Overview:
In this project, we performed a deep exploratory data analysis (EDA) on the Netflix dataset (8K+ entries from Kaggle). We uncovered patterns by analyzing film types, release years, genres, countries, and ratings using Python, Pandas, and visualization tools like Matplotlib, Seaborn, and Plotly.
Key Highlights:
- Cleaned and structured the dataset: handled missing dates, normalized genres, and corrected release years.
- Visualized content trends over time—growth of TV shows vs. movies and genre distribution across countries.
- Identified top-performing genres, trending directors, and global release patterns.
Technologies Used:
Python · Pandas · Matplotlib · Seaborn · Plotly · Tableau
Outcome & Learnings:
Enabled decision-makers to understand content evolution and geographic preferences. The dashboard clearly illustrated the rise of TV content after 2015 and highlighted genre popularity over time, aiding strategic planning and content alignment for entertainment platforms.
